Electromagnetism-like algorithms for optimized tool path planning in 5-axis flank machining

Optimization of tool path planning using metaheuristic algorithms such as ant colony systems (ACS) and particle swarm optimization (PSO) provides a feasible approach to reduce geometrical machining errors in 5-axis flank machining of ruled surfaces. The optimal solutions of these algorithms exhibit an unsatisfactory quality in a high-dimensional search space. In this study, various algorithms derived from the electromagnetism-like mechanism (EM) were applied. The test results of representative surfaces showed that all EM-based methods yield more effective optimal solutions than does PSO, despite a longer search time. A new EM-MSS (electromagnetism-like mechanism with move solution screening) algorithm produces the most favorable results by ensuring the continuous improvement of new searches. Incorporating an SPSA (simultaneous perturbation stochastic approximation) technique further improves the search results with effective initial solutions. This work enhances the practical values of tool path planning by providing a satisfactory machining quality.     

Intelligent Information‐Centric Networking routing scheme under imprecise information

Information‐Centric Networking (ICN) has been accepted to overcome some weaknesses of the current Internet architecture, showing that “what is being exchanged” is more important than “who are exchanging information.” Given the inadequate considerations on Quality of Service (QoS) and energy saving in ICN routing, we propose in this paper a routing algorithm to enhance the two aspects. At first, on one hand, Cauchy distribution is used as a fuzzy model to evaluate users' QoS requirements, such as bandwidth, delay, and error rate; on the other hand, we formulate energy saving problem to evaluate the green quality of routing algorithm. Then, we design a link selection approach by considering QoS and energy saving, which belongs to a multi‐objective decision problem resolved by intelligent drops algorithm. Finally, we implement the proposed algorithm and compare it with the famous adaptive forwarding mechanism in terms of some significant metrics, and the experimental results reveal that the proposed algorithm is more efficient.     

Three-phase four-wire shunt active power filter based on the SOGI filter and Lyapunov function for DC bus control

The three-phase four-wire shunt active power filter (SAPF) was developed to suppress the harmonic currents generated by nonlinear loads, and for the compensation of unbalanced nonlinear load currents, reactive power, and the harmonic neutral current. In this work, we consider instantaneous reactive power theory (PQ theory) for reference current identification based on the following two algorithms: the classic low-pass filter (LPF) and the second-order generalized integrator (SOGI) filter. Furthermore, since an important process in SAPF control is the regulation of the DC bus voltage at the capacitor, a new controller based on the Lyapunov function is also proposed. A complete simulation of the resultant active filtering system confirms its validity, which uses the SOGI filter to extract the reference currents from the distorted line currents, compared with the traditional PQ theory based on LPF. In addition, the simulation performed also demonstrates the superiority of the proposed approach, for DC bus voltage control based on the Lyapunov function, compared with the traditional proportional-integral (PI) controller. Both novel approaches contribute towards an improvement in the overall performance of the system, which consists of a small rise and settling time, a very low or nonexistent overshoot, and the minimization of the total harmonic distortion (THD).     

La0.6Sr0.4Co0.2Fe0.8O3-δ nanofiber cathode for intermediate-temperature solid oxide fuel cells by water-based sol-gel electrospinning: Synthesis and electrochemical behaviour

Water-based sol-gel electrospinning is employed to manufacture perovskite oxide La_0.6Sr_0.4Co_0.2Fe_0.8O_3-δ (LSCF) nanofiber cathodes for intermediate-temperature solid oxide fuel cells. LSCF fibrous scaffolds are synthesized through electrospinning of a sol-gel solution employing water as the only solvent. Morphological characterizations demonstrate that the LSCF fibers have highly crystalline structure with uniform elemental distribution. After heat treatment, the average fiber diameter is 250 nm and the porosity of the nanofiber tissue is 37.5 %. The heat treated LSCF nanofibers are applied directly onto a Ce_0.9Gd_0.1O_1.95 (CGO) electrolyte disk to form a symmetrical cell. Electrochemical characterization is carried out through electrochemical impedance spectroscopy (EIS) in the temperature range 550?°C–950?°C, and reproducibility of the electrochemical performance for a series of cells is demonstrated. At 650?°C, the average measured polarization resistance R_p is 1.0 Ω cm². Measured performance decay is 1 % during the first 33?h of operation at 750?°C, followed by an additional 0.7 % over the subsequent 70?h.     

Tough salami-inspired Cf/ZrB2 UHTCMCs produced by electrophoretic deposition

One of the biggest challenges of the materials science is the mutual exclusion of strength and toughness. This issue was minimized by mimicking the natural structural materials. To date, few efforts were done regarding materials that should be used in harsh environments. In this work we present novel continuous carbon fiber reinforced ultra-high-temperature ceramic matrix composites (UHTCMCs) for aerospace featuring optimized fiber/matrix interfaces and fibers distribution. The microstructures – produced by electrophoretic deposition of ZrB₂ on unidirectional carbon fibers followed by ZrB₂ infiltration and hot pressing – show a maximum flexural strength and fracture toughness of 330 MPa and 14 MPa m^1/2, respectively. Fracture surfaces are investigated to understand the mechanisms that affect strength and toughness. The EPD technique allows the achievement of a peculiar salami-inspired architecture alternating strong and weak interfaces.     

The potential of energy flexibility of space heating and cooling in Portugal

This study assesses the potential of energy flexibility of space heating and cooling for a typical household under different geographical conditions in Portugal. The proposed approach modifies the demand through the optimization of the thermostat settings using a genetic algorithm to reduce either operational costs or interaction with the grid. The results show that the used energy flexibility indicator expresses the available potential and that flexibility depends on several factors, namely: i) thermal inertia of the archetypical household; ii) the time of use electricity tariffs; iii) users’ comfort boundaries; and iv) the geographical location of the houses.     

Pt–Ru nanoparticles anchored on poly(brilliant cresyl blue) as a new polymeric support: Application as an efficient electrocatalyst in methanol oxidation reaction

The glassy carbon electrode is modified by poly(brilliant cresyl blue) (PBCB) to be applied as a new green and efficient platform for Pt and Pt–Ru alloy nanoparticles deposition. Surface composition, morphology and catalytic activity of these modified electrodes towards methanol oxidation are assessed by applying X-ray diffraction, field emission scanning electron microscopy, cyclic voltammetry and electrochemical impedance spectroscopy techniques. The X-ray diffraction patterns reveal that the highly crystalline Pt and Pt–Ru alloy and RuO₂ nanoparticles with low crystallinity are deposited on the PBCB modified glassy carbon electrodes. The microscopic images indicate smaller size and better distribution of deposited nanoparticles on the surface of PBCB modified electrodes. Cyclic voltammetry and electrochemical impedance spectroscopy results reveal that PBCB supported Pt and Pt–Ru nanoparticles have better electrocatalytic performance and durability towards methanol oxidation rather than the unsupported nanoparticles. From the obtained results it can be concluded that the presence of PBCB not only improves the stability of nanoparticles on the surface, but also leads to the formation of smaller size and more uniform distribution of nanoparticles on the surface, which, in turn, cause the nanoparticles to provide a higher accessible surface area and more active centers for the oxidation of methanol. The results will be valuable in extending the applications of this polymer in surface modification steps and in developing promising catalyst supports to be applied in direct methanol fuel cells.     

Ions motion algorithm for solving optimization problems

This paper proposes a novel optimization algorithm inspired by the ions motion in nature. In fact, the proposed algorithm mimics the attraction and repulsion of anions and cations to perform optimization. The proposed algorithm is designed in such a way to have the least tuning parameters, low computational complexity, fast convergence, and high local optima avoidance. The performance of this algorithm is benchmarked on 10 standard test functions and compared to four well-known algorithms in the literature. The results demonstrate that the proposed algorithm is able to show very competitive results and has merits in solving challenging optimization problems.     

Robust Control of Permanent Magnet Synchronous Motors

In this paper, permanent magnet synchronous motors (PMSMs) are investigated. According to the feature of PMSMs, a novel state equation of PMSMs is obtained by choosing suitable state variables. Based on the state equation, robust controllers are designed via interval matrix and PI control idea. In terms of bilinear matrix inequations, sufficient conditions for the existence of the robust controller are derived. In order to reduce the conservation and the dependence on parameter, the control inputs of PMSMs are divided into two parts, a feedforward control input and a feedback control input, and relevant sufficient conditions for the existence of the controller are obtained. Because of the suitable choice of state variables, the proposed control strategies can cope with the load uncertainty and have robustness for disturbance. Finally, simulations are carried out via Matlab/Simulink soft to verify the effectiveness of the proposed control strategies. The performance of the proposed control strategies are demonstrated by the simulation results.      

Superior foetal electrocardiogram signal elicitation using a novel artificial intelligent Bayesian methodology

Innumerable casualties due to intrauterine hypoxia are a major worry during prenatal phase besides advanced patient monitoring with latest science and technology. Hence, the analysis of foetal electrocardiogram (fECG) signals is very vital in order to evaluate the foetal heart status for timely recognition of cardiac abnormalities. Regrettably, the latest technology in the cutting edge field of biomedical signal processing does not seem to yield the desired quality of fECG signals required by physicians, which is the major cause for the pathetic condition. The focus of this work is to extort non-invasive fECG signal with highest possible quality with a motive to support physicians in utilizing the methodology for the latest intrapartum monitoring technique called STAN (ST analysis) for forecasting intrapartum foetal hypoxia. However, the critical quandary is that the non-invasive fECG signals recorded from the maternal abdomen are affected by several interferences like power line interference, baseline drift interference, electrode motion interference, muscle movement interference and the maternal electrocardiogram (mECG) being the dominant interference. A novel hybrid methodology called BANFIS (Bayesian adaptive neuro fuzzy inference system) is proposed. The BANFIS includes a Bayesian filter and an adaptive neuro fuzzy filter for mECG elimination and non-linear artefacts removal to yield high quality fECG signal. Kalman filtering frame work has been utilized to estimate the nonlinear transformed mECG component in the abdominal electrocardiogram (aECG). The adaptive neuro fuzzy filter is employed to discover the nonlinearity of the nonlinear transformed version of mECG and to align the estimated mECG signal with the maternal component in the aECG signal for annulment. The outcomes of the investigation by the proposed BANFIS system proved valuable for STAN system for efficient prediction of foetal hypoxia.